Vol.:(0123456789) Fuzzy Optimization and Decision Making https://doi.org/10.1007/s10700-023-09409-3 1 3 Medical health resources allocation evaluation in public health emergencies by an improved ORESTE method with linguistic preference orderings Gou Xunjie 1  · Fumin Deng 1  · Xu Xinru 1  · Wei Zhou 2  · Enrique Herrera‑Viedma 3 Accepted: 18 April 2023 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023 Abstract As an important major public health emergency, COVID-19 broke out more than two years. At present, China has entered the post-epidemic era. However, it is still necessary to study the medical health resource allocation in public health emergen- cies. Therefore, the evaluation of medical health resources allocation is important. Firstly, we use two kinds of linguistic preference orderings (LPOs) to represent experts’ opinions when evaluating the medical health resources allocation in pub- lic health emergencies. Then, a novel ORESTE method with LPOs is developed to solve multiple criteria decision-making (MCDM) problems. Additionally, we apply the proposed ORESTE method to solve a practical MCDM problem involv- ing the medical health resources allocation in public health emergencies. Finally, some comparative analyses among the proposed ORESTE method and some exist- ing methods under a double hierarchy linguistic environment are set up, and some discussions are summarized to show the validity and applicability of the proposed novel ORESTE method. Keywords Linguistic preference orderings · ORESTE · Multiple criteria decision- making · Medical health resources allocation · Public health emergencies * Fumin Deng dengfm@scu.edu.cn Wei Zhou zw453@163.com 1 Business School, Sichuan University, Chengdu 610065, China 2 School of Finance, Yunnan University of Finance and Economics, Kunming 650221, China 3 Andalusian Research Institute in Data Science and Computational Intelligence, 18071 Granada, Spain